Research
Research
My research interests are in (1) using experimental and modeling work to monitor and evaluate stream quality, and using data-driven approaches to better inform and enhance water quality models; (2) using optimization techniques to identify optimal and sustainable land management practices; (3) evaluate the benefits of best managements practices and understanding their impacts on stream pollutant dynamics; and (3) developing decision-support and outreach tools to better communicate our research findings to stakeholders and the larger community. Some of the projects that I have worked on previously are listed below.
My PhD research involved developing a comprehensive and user-friendly stream solute transport model by integrating knowledge from existing water quality models. The interface (built on MATLAB programming platform) is a stand-alone model that was further incorporated into the Soil and Water Assessment Tool (SWAT) model for improving water quality predictions at watershed-scale. Access the open-source code on GitHub here.
Using the Soil and Water Assessment Tool (SWAT) model, I looked at watershed-scale impacts of land management, and improving the nutrient transport representation in the model for better water quality predictions. I have conducted model calibration and validation (for streamflow, sediment, and nutrients) on multiple watersheds in US and Germany . The calibrated models were used to study impacts of different crops and agricultural practices on water quantity and quality.
Using an efficient framework combining SWAT simulations and optimization algorithms, the cropping pattern in St. Joseph River watershed (USA) was spatially optimized to (1) increase biofuel production (using Switchgrass, Miscanthus, and corn stover), and (2) reduce downstream water pollution, within the constraints of ensuring food security and reducing food versus fuel competition.
A framework coupling hydrological, crop yield, land-use, and economic models were used to evaluate impact of unsustainable groundwater restrictions on crop production in the Western U.S states. We found that deficit irrigation can be used as an excellent mitigation strategy in southwestern states to maximize profits under water stress. This work is funded by the Department of Energy through the PCHES project.
I work on developing models to predict duckweed growth under different temperatures, light intensities, and nutrient concentrations, which are validated through data collected using laboratory experiments. I am also interested in looking at changes in duckweed nutrient uptake and protein accumulation under different environmental conditions. This work is part of a project funded by Open Philanthropy that looks at emergency food resilience in the face of global catastrophic events.
As part of an an NSF-funded project, I explored the potential of growing duckweed on dairy manure and using it as dairy feed and fertilizer-substitute, essentially transforming the nitrogen bioeconomy and promoting a circular agriculture system. Within this project, I specifically focused on how duckweed can be used as a substitute for soybean-based protein feed in order to improve water quality in the Chesapeake Bay Watershed.
My recent research interests also include large-scale systems modeling to evaluate sustainable interventions at the water-energy-food (WEF) nexus. I have used systems modeling software that integrate physical and socioeconomic elements to represent interlinkages between various components of the WEF nexus.
In addition to modeling integrated duckweed-wastewater treatment systems at watershed-scale, I am also interested in conducting life cycle assessments on these systems at a farm-scale to evaluate short- and long-term environmental impacts and benefits. I have incorporated LCA studies to (1) the WEF-nexus based system modeling work and (2) the emergency food resilience project (both listed above) for an integrated household-scale duckweed farming system.